Definition
This topic is related to applications of emerging patterns in the bioinformatics field, in particular for in-silico cancer diagnosis by mining emerging patterns from large scale microarray gene expression data.
Key Points
The contemporary gene expression profiling technologies such as cDNA microarray chips and Affymetrics DNA microarry chips can measure the expression levels of thousands even tens of thousands of genes simultaneously. This provides a great opportunity to identify specific genes or gene groups that are responsible for a particular disease, for example, the subtypes of childhood leukemia disease. Reference [3] proposed to use emerging patterns to capture the signature patterns between the gene expression profiles of colon tumor cells and normal cells. This was the first bioinformatics work studying how gene groups and their expression intervals signify the difference between diseased and normal cells. That paper also proposed to design treatment plans to cure...
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Recommended Reading
Boulesteix A-L, Tutz G, Strimmer K. A CART-based approach to discover emerging patterns in microarray data. Bioinformatics. 2003;19(18):2465–72.
Li J, Liu H, Downing JR, Eng-Juh YA, Wong L. Simple rules underlying gene expression profiles of more than six subtypes of acute lymphoblastic leukemia (ALL) patients. Bioinformatics. 2003;19:71–8.
Li J, Wong L. Identifying good diagnostic genes or genes groups from gene expression data by using the concept of emerging patterns. Bioinformatics. 2002;18:725–34.
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Dong, G., Li, J. (2016). Applications of Emerging Patterns for Microarray Gene Expression Data Analysis. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_5003-2
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DOI: https://doi.org/10.1007/978-1-4899-7993-3_5003-2
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Publisher Name: Springer, New York, NY
Online ISBN: 978-1-4899-7993-3
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